Improving Component Substitution Pan-Sharpening Through Refinement of the Injection Detail

摘要

This article presents a novel strategy for improving the well-established component substitution-based multispectral image fusion methods, because the fused results obtained by component substitution methods tend to exhibit significant spectral distortion. The main cause of spectral distortion is analyzed and discussed based on the component substitution method's general model. An improved scheme is derived from the sensitivity imaging model to refine the approximate spatial detail and obtain one that is almost ideal. The experimental results on two data sets show that when it has been integrated into the Gram-Schmidt method and the generalized intensity-hue-saturation method, the proposed scheme allows the production of fused images of the same spatial sharpness as standard implementations but with significantly increased spectral quality. Quantitative scores and visual inspection at full resolution and spatially reduced resolution confirm the superiority of the improved methods over the conventional algorithms.